**Paper**:
[anonymized authors] (2023). Evidence for infant-directed speech preference is consistent across large-scale, multi-site replication and meta-analysis.
**Abstract**:
There is substantial evidence that infants prefer infant-directed speech (IDS) to adult-directed speech (ADS). The strongest evidence for this claim has come from two large-scale investigations: i) a community-augmented meta-analysis of published behavioral studies and ii) a large-scale multi-lab replication study. In this paper, we aim to improve our understanding of the IDS preference and its boundary conditions by combining and comparing these two data sources across key population and design characteristics of the underlying studies. Our analyses reveal that both the meta-analysis and multi-lab replication show moderate effect sizes (d = 0.35 for both estimates) and that both of these effects persist when relevant study-level moderators are added to the models (i.e., experimental methods, infant ages, and native languages). However, while the overall effect size estimates were similar, the two sources diverged in the effects of key moderators: both infant age and experimental method predicted IDS preference in the multi-lab replication study, but showed no effect in the meta-analysis. These results demonstrate that the IDS preference generalizes across a variety of experimental conditions and sampling characteristics, while simultaneously identifying key differences in the empirical picture offered by each source individually and pinpointing areas where substantial uncertainty remains about the influence of theoretically central moderators on IDS preference. Overall, our results show how meta-analyses and multi-lab replications can be used in tandem to understand the robustness and generalizability of developmental phenomena.
**Repository Materials**:
- **GitHub**: The repository is linked to the GitHub repository including all data, code, and model outputs, and figures.
- **data_analysis**: This folder contains IDSPreference_ManyBabiesMeta.zip. This is a zipped folder of the GitHub repository, including data, code, model outputs, and figures for the main manuscript. See the ReadME for more information about the folder structure.
